Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate a dynamic cross-platform ask interface and utilize a cross-platform language processing model to provide platform-specific, contextually based responses to natural language digital text queries. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to extract registered intents from digital text queries to identify platform-specific configurations associated with the registered intents. Utilizing the platform-specific configurations, the disclosed systems can generate tailored platform-specific requests for information, as well as customized end-user search results that cause client devices to efficiently, accurately, and flexibly render platform-specific search results.

Abstract: Implementations include querying metadata of data objects to define a sub-set of data objects, each data object in the sub-set of data objects including a generic text field and/or an attachment field, and, for each data object in the sub-set of data objects, processing historical data of a data object to identify a set of data types, the historical data stored within a field of a table of a database system, providing a recommendation for a first extension corresponding to a first data type, and receiving user input indicating acceptance of the recommendation for the first extension and, in response, automatically providing extension code that is executable to add a field extension to the table and to modify a UI of an application for input of values corresponding to the first data type, and executing the extension code to deploy the extension and to modify the UI.

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.

Abstract: A method including analyzing the query data to formulate one or more groups of synonym candidates, wherein each synonym in the one or more groups of synonym candidates is categorized in one or more synonym candidate categories. Reformulating the first search query by removing at least one synonym candidate from the first group of synonym candidates to form a first set of synonyms such that each synonym in the first set of synonyms is categorized in the synonym candidate category that matches the search query category of the search query, wherein the at least one synonym candidate removed from the first group of synonym candidates is not categorized in the synonym candidate category.

Abstract: Methods, systems, and devices supporting primitive-based query generation are described. A database system may receive a natural language query associated with a subset of data sets stored at the database system, determine a set of tokens included in the natural language query, and label one or more tokens of the set of tokens with one or more primitives from a set of supported primitives associated with the subset of data sets. The database system may determine a set of higher order concepts corresponding to query operations, query conditions, or both based on the one or more labeled tokens. The database system may train a neural network to learn a grammatical structure of the natural language query and generate a database query for querying the database system based on the one or more labeled tokens, the set of higher order concepts, and the neural network.

Abstract: A question answering (QA) system comprising memory for storing instructions, and a processor configured to execute the instructions to ingest source documents that include structured data and unstructured data to create a knowledge base, wherein the unstructured data includes table data; create table annotations to represent the table data; store the ingested structured data, unstructured data, and the table annotations in the knowledge base; and determine answers to questions using the knowledge base.

Abstract: A computer device receives a request to search a corpus of documents for an entity, wherein the request includes a non-name identifier of the entity. The computing device identifies entries of text within the corpus of documents that reference the non-name identifier. The computing device applies natural language processing (NLP) to content associated with the identified entries within the corpus of documents, wherein the NLP identifies candidate entities associated with the non-name identifier. The computing device selects an entity from the candidate entities based, at least in part, on distances between the candidate entities and references to the non-name identifier in the identified entries. The computing device returns the selected entity to a submitter of the request.

Abstract: Techniques and solutions are described for copying data from a source client to a target client. It may be selected, such as by a user, whether a full copy or a partial copy of a set of source client data should be made. If a partial copy is selected, a set of file types is provided. The file types can be used to define files that should be included in, or excluded from, the copy. A data source of the source client is analyzed to determine data associated with a file type that is to be included in a copy, or is associated with a file type that is not indicated as to be excluded from the copy. The determined data is copied from the source client to the target client.

Abstract: Systems, apparatus, methods, and articles of manufacture provide for generation, execution, and visualization of data queries (e.g., SQL statements) and their results, based on natural language input from a user. In one example implementation, a dashboard system provides a voting lounge and personalized and crowdsourced dashboards.

Abstract: Techniques are disclosed relating to building an in-memory multi-level data structure useable to determine presence or absence of key ranges in files consisting of database records. In various embodiments, a computer system operates a database, including maintaining a set of records having a set of corresponding keys that are accessible in key-sorted order and generates a multi-level data structure that facilitates key range lookups against the set of records. The generating may include accessing ones of the set of keys in key-sorted order and determining, for a particular accessed key that includes a set of characters, an intermediate level within the multi-level data structure and a subset of the characters of the particular accessed key for insertion. The computer system may insert, starting at the intermediate level, information that identifies the subset of characters, with the inserting being performed without traversing any levels before the intermediate level.

Abstract: The present disclosure generally relates to the connection, operation, automation, and autonomation of disparate computing systems, networks, and databases. The present disclosure further relates to a method for operating a plurality of legacy systems, comprising: receiving a user input string from a user; parsing the user input string into a plurality of terms; generating, for each of the plurality of legacy systems, based on the user input string, one or more legacy input strings, each of the one or more legacy input strings being executable by each of the plurality of legacy systems and comprising a syntactical arrangement of one or more of the plurality of terms; and instructing the plurality of legacy systems to execute the one or more legacy input strings.

Abstract: A computer-implemented method for generating a question from an abstracted template is described. A non-limiting example of the computer-implemented method includes receiving, by a processor, a question. The method parses, by the processor, the question into a parse tree and abstracts, by the processor, an abstracted template from the parse tree. The method receives, by the processor, a domain schema and a domain knowledge base and generates, by the processor, a new question based on the abstracted template, the domain schema, and the domain knowledge base.

Abstract: The present disclosure relates to frameworks and methodologies for enabling categorisation and/or searching of digitised information, including clinical report data. Embodiments of the invention have been particularly developed to assist categorisation of digitised information, such as clinical report data, in a streamlined manner based on a pre existing set of classification codes. This, in some embodiments, enables the discovery and extraction of meaningful patterns from unstructured clinical reports. Further embodiments of the invention have been particularly developed to assist in the discovery and extraction of meaningful patterns from an unstructured set of digitised information such as unstructured clinical reports. While some embodiments will be described herein with particular reference to those applications, it will be appreciated that the invention is not limited to such a field of use, and is applicable in broader contexts.

Abstract: In accordance with embodiments, there are provided techniques for managing functionality changes of a database platform of a service provider. The techniques facilitate implementing changes to the database platform while minimizing work flow reductions to users of the database platform. To that end, one embodiment of the present invention delays implementation of the changes for a duration of time to provide users of the database platform an opportunity to adjust behavioral interaction with the database platform. In accordance with another embodiment of the present invention, users may implement the functional changes to determine any adverse impact on work flow, before the functional changes become permanent. In another embodiment, the users may be afforded an opportunity to selectively enable and disable the functionality changes before the duration of time expires.

Abstract: A database replication system comprises a plurality of replica data nodes and a master data node. The master data node is configured with an acknowledgement requirement that comprises an acknowledgement threshold that is less than a total number of data nodes in a plurality of data nodes. The master data node is configured to send, to the plurality of replica data nodes, a transaction log record that includes an update to data in the master database that has not been committed to the master database, receive acknowledgements of the transaction log records and based on a determination that the received acknowledgements of the transaction log record meet the acknowledgement requirement, set the transaction log record as a master node last acknowledged transaction log record in a master node transaction log. The last acknowledged transaction log record can be used to control recovery.

Abstract: In one embodiment, a method includes receiving, from a client system, a text input comprising one or more n-grams, determining, using a deep-learning model, a vector representation of the text input based on the one or more n-grams, determining an embedding of the vector representation of the text input in a d-dimensional embedding space, identifying one or more labels based on, for each of the one or more labels, a respective similarity of an embedding of a vector representation of the label in the embedding space to the embedding of the vector representation of the text input, and sending, to the client system in response to the received text input, instructions for presenting a user interface comprising one or more of the identified labels as suggested labels.

Abstract: Object scriptability methods and system are described herein. The method includes generating a graph-based data structure including a plurality of nodes, where each node from the plurality of nodes represents a respective data-analysis object in a data analysis system, where each node from the plurality of nodes is connected to at least one other node from the plurality of nodes by an edge, where the edge represents a relationship between the respective objects in the data analysis system, and where generating the graph-based data structure includes receiving a high-level language script describing at least one data-analysis object, and generating at least one node from the plurality of nodes in accordance with the high-level language script.

Abstract: An analytics engine is described that can receive data associated with use of a content item in a content management system and measure and measure a use of content management system resources required to maintain the content item. Values of a usage metric can be assigned to the content item based on the received data associated with the use of the content item. A database schema can be generated by the analytics engine that is configured to reduce the use of content management system resources required to maintain the content item. The database schema can be provided to the content management system for implementation in a database associated with the content management system.

Abstract: A method, system and computer program product for forecasting a storage requirement of a database management system (DBMS). The storage-related operations (e.g., create, delete, update) of the applications connected to the DBMS are monitored. The impact on the storage usage of the DBMS based on these storage-related operations performed by the applications is monitored. Furthermore, the applications are categorized into groups of applications based on the monitored storage-related operations. A mathematical model is then built to forecast the storage requirement of the DBMS based on the monitored impact on the storage usage of the DBMS by the monitored storage-related operations of the applications and the categorization of the applications. The storage requirement of the DBMS is then forecasted based on the built mathematical model. In this manner, the storage requirements of the DBMS may be accurately predicted to ensure that there is available storage thereby preventing performance degradation.

Abstract: A process for recommending pre-constructed queries in data analytics includes writing different records to a correlation data structure correlating different data classifications of data to different queries and, subsequent to the writing, establishing a communicative connection by a data analytics application to an underlying database. Thereafter, a data model for data in the database may be constructed in the data analytics application and at least one of the different queries may be selected in the correlation data structure that correlates to the classification of the data in the data model. Finally, the selected one of the different queries may be displayed in the data analytics application to an end user so as to provide an intelligent recommendation for the addition of the selected one of the different queries without requiring the end user to alone and without assistance discover the suitability of the selected one of the different queries.